Deep learning is white hot – both in buzz and in actual value. This recently-proven collection of advanced neural network methods scales machine learning to a new level of capabilities – namely, achieving high performance for large-signal input problems, such as for the classification of images (self-driving cars, medical images), sound (speech recognition, speaker recognition), text (document classification), and even “standard” business problems, e.g., by processing high dimensional clickstreams.

To help catalyze deep learning’s commercial deployment, we’re introducing the all-new Deep Learning World conference, June 3-7 in Las Vegas. DLW is part of Mega-PAW Vegas, which also features four (4) concurrent Predictive Analytics World conferences: PAW Business, PAW Financial, PAW Healthcare, and PAW Manufacturing.

The inaugural Deep Learning World takes place June 3-7, 2018 in Las Vegas

Neural networks were already exciting 21 years ago, when I first taught grad students about them in my machine learning course at Columbia University. They weren’t “deep” – they were shallow, typically with only one intermediate layer between the input and output layers. And yet, for many domains, they were the leading option. Back then, shallow neural networks were already driving cars around Carnegie Mellon and doing face recognition. Now that we can scale them to harness the power of many intermediate layers, the potential has multiplied many times over.

No discussion of deep learning would be complete without mentioning Google’s unmatched contributions. Like Microsoft, their work begins internally. With deep learning, Google has made significant improvements to most of our main products, including Android, Apps, Maps, Speech, Search, Translation, and YouTube. For example, Gmail now intercepts 99.9% of spam. And your unlabeled photos kept in Google Photos are searchable by ad hoc terms such as, “hug.”

If you’re climbing the learning curve of deep learning, check out Google’s Distill, which creatively illustrate the technical concepts, and Google’s TensorFlow playground interactive demo lets you play, visualize, and learn. See also Google Brain’s Big Picture Group, which “explores how information visualization can make complex data accessible, useful, and even fun.” Also, I recommend thesethreevideos of Google talks.